Best Artificial Intelligence Software for Linux - Page 4
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Compare the Top Artificial Intelligence Software for Linux as of December 2025 - Page 4
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This a list of Artificial Intelligence software for Linux. Use the filters on the left to add additional filters for products that have integrations with Linux. View the products that work with Linux in the table below.
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1
Reflex
Pynecone
Reflex is an open source framework that empowers Python developers to build full-stack web applications entirely in pure Python, eliminating the need for JavaScript or complex frontend frameworks. With Reflex, you can write, test, and refine your app using just Python, making it fast, flexible, and scalable. It features an AI Builder that allows you to describe your app idea, and it will generate a working Python app instantly, complete with backend, frontend, and database integration. Reflex's architecture compiles the frontend down to a single-page Next.js app, while the backend is powered by FastAPI, with communication handled via WebSockets. This setup ensures that all the app logic and state management stay in Python and run on the server. The framework offers over 60 built-in components based on Radix UI and supports custom React components, enabling developers to create complex UIs without writing HTML or CSS.Starting Price: $20 per month -
2
Piper TTS
Rhasspy
Piper is a fast, local neural text-to-speech (TTS) system optimized for devices like the Raspberry Pi 4, designed to deliver high-quality speech synthesis without relying on cloud services. It utilizes neural network models trained with VITS and exported to ONNX Runtime, enabling efficient and natural-sounding speech generation. Piper supports a wide range of languages, including English (US and UK), Spanish (Spain and Mexico), French, German, and many others, with voices available for download. Users can run Piper via the command line or integrate it into Python applications using the piper-tts package. The system allows for real-time audio streaming, JSON input for batch processing, and supports multi-speaker models. Piper relies on espeak-ng for phoneme generation, converting text into phonemes before synthesizing speech. It is employed in various projects such as Home Assistant, Rhasspy 3, NVDA, and others.Starting Price: Free -
3
LiteRT
Google
LiteRT (Lite Runtime), formerly known as TensorFlow Lite, is Google's high-performance runtime for on-device AI. It enables developers to deploy machine learning models across various platforms and microcontrollers. LiteRT supports models from TensorFlow, PyTorch, and JAX, converting them into the efficient FlatBuffers format (.tflite) for optimized on-device inference. Key features include low latency, enhanced privacy by processing data locally, reduced model and binary sizes, and efficient power consumption. The runtime offers SDKs in multiple languages such as Java/Kotlin, Swift, Objective-C, C++, and Python, facilitating integration into diverse applications. Hardware acceleration is achieved through delegates like GPU and iOS Core ML, improving performance on supported devices. LiteRT Next, currently in alpha, introduces a new set of APIs that streamline on-device hardware acceleration.Starting Price: Free -
4
Kiro
Amazon Web Services
Kiro is an AI‑powered integrated development environment that brings structure to AI‑driven coding by converting natural‑language prompts into clear requirements, system designs, and discrete implementation tasks validated by robust tests. Built from the ground up for agentic workflows, it features spec‑driven development, multimodal chat, “agent hooks” that trigger background tasks on events like file saves, and an autopilot mode that autonomously runs large scripts while keeping you in control. With smart context management, Kiro reduces repetitive prompts and helps implement complex features across large codebases. Native MCP integrations let you connect to documentation, databases, and APIs, and you can guide development with images of UI designs or architecture diagrams. Enterprise‑grade security and privacy ensure safe deployment, while support for Claude Sonnet models, Open VSX plugins, and existing VS Code settings delivers a familiar yet AI‑supercharged experience.Starting Price: $19 per month -
5
Void Editor
Void Editor
Void is an open source AI code editor and Cursor alternative built as a fork of VS Code, enabling developers to write code with advanced AI assistance while retaining full control over their data. It supports seamless integration with any large language model, such as DeepSeek, Llama, Qwen, Gemini, Claude, and Grok, connecting directly without routing through a private backend. Core features include tab‑triggered autocomplete, inline quick edit, and a versatile AI chat interface offering normal chat, a restricted gather mode for read/search-only tasks, and an agent mode that automates file and folder operations, terminal commands, and MCP tool access. Void delivers high‑performance operations, including fast apply on files with thousands of lines, alongside checkpoint management for model updates, native tool execution, and lint error detection. Developers can transfer all themes, keybindings, and settings from VS Code in one click and host models locally or via the cloud.Starting Price: Free -
6
Parlant
Parlant
Parlant is a production-ready, open source framework for building compliant AI chat agents that reliably follow instructions and scale with complexity. It enables developers to create adaptive, iterative, and explainable conversational agents using natural-language behavior modeling, including guidelines, journeys, canned responses, retrievers, glossaries, and tools, all versionable via Git. Its guidelines let you nudge agent behavior contextually and precisely, while journeys define multi-step interaction flows; canned responses ensure consistency in high-risk scenarios; and explainability tools provide clear visibility into why each decision was made. Tools require matching guidelines to execute, cleanly separating business logic from conversation behavior, enabling developers and business experts to collaborate independently. Built-in features like session persistence, tool result tracking across sessions, and a drop-in React chat widget make it easy to install.Starting Price: Free -
7
Foxglove
Foxglove
Foxglove is a visualization, observability, and data management platform purpose-built for robotics and embodied AI development that centralizes and simplifies working with large, multimodal temporal datasets, including time series, sensor logs, imagery, lidar/point clouds, geospatial maps, and more, in a single, integrated workspace. It enables engineers to record, import, organize, stream, and visualize both live and recorded data from robots using intuitive, customizable dashboards with interactive panels for 3D scenes, plots, raw messages, images, and maps, helping users understand how robots sense, think, and act. Foxglove supports real-time connections to systems like ROS and ROS 2 via bridges and web sockets, enables cross-platform workflows (desktop app for Linux, Windows, and macOS), and facilitates rapid analysis, debugging, and performance optimization by synchronizing diverse data sources in time and space.Starting Price: $18 per month -
8
Wing Python IDE
Wingware
Wing Python IDE was designed from the ground up for Python, to bring you a more productive development experience. Type less and let Wing worry about the details. Get immediate feedback by writing your Python code interactively in the live runtime. Easily navigate code and documentation. Avoid common errors and find problems early with assistance from Wing's deep Python code analysis. Keep code clean with smart refactoring and code quality inspection. Debug any Python code. Inspect debug data and try out bug fixes interactively without restarting your app. Work locally or on a remote host, VM, or container. Wingware's 21 years of Python IDE experience bring you a more Pythonic development environment. Wing was designed from the ground up for Python, written in Python, and is extensible with Python. So you can be more productive. -
9
Eclipse Theia
Eclipse Foundation
Eclipse Theia is an extensible platform to develop multi-language Cloud & Desktop IDEs with state-of-the-art web technologies. Not sure whether you need a web or desktop version or both? With Theia you can develop one IDE and run it in browsers or native desktop application from a single source. The Theia project is hosted at the Eclipse Foundation, a not-for-profit corporation, and is developed by a diverse community. Unlike other "open-source" projects, projects hosted at an Open-Source Foundation are protected against single-vendor decisions against the interest of the diverse community. Theia is designed in a modular way to allow extenders and adopters customizing and extending every aspect of it. Composing a custom IDE-like product is as easy as listing all needed extensions in a package.json file. Adding new functionality by implementing your own extensions is easy, too and provides all the flexibility you need.Starting Price: $0 -
10
CLion
JetBrains
Who wouldn’t like to code at the speed of thought while the IDE does all the mundane development tasks for them? But is that really possible for a tricky language like C++, what with its modern standards and heavily templated libraries? Why, yes, yes it is! See it to believe it. Generate tons of boilerplate code instantly. Override and implement functions with simple shortcuts. Generate constructors and destructors, getters and setters, and equality, relational, and stream output operators. Wrap a block of code with a statement, or generate a declaration from a usage. Create custom live templates to reuse typical code blocks across your code base to save time and maintain a consistent style. Rename symbols; inline a function, variable, or macro; move members through the hierarchy; change function signatures; and extract functions, variables, parameters, or a typedef.Starting Price: $8.90 per month -
11
IntelliCode
Microsoft
Visual Studio IntelliCode: AI-assisted development. IntelliCode saves you time by putting what you’re most likely to use at the top of your completion list. IntelliCode recommendations are based on thousands of open source projects on GitHub each with over 100 stars. When combined with the context of your code, the completion list is tailored to promote common practices. IntelliCode isn’t limited to statement completion. Signature help also recommends the most likely overload for your context. IntelliCode can provide recommendations based on your code and seamlessly share them across your team. With this preview feature, you can build a team model to provide recommendations on code that isn’t in the open source domain, such as methods on your own utility classes or domain specific library calls. Integrate our build task into your pipeline to keep your team completions up to date with repository changes. -
12
Tecton
Tecton
Deploy machine learning applications to production in minutes, rather than months. Automate the transformation of raw data, generate training data sets, and serve features for online inference at scale. Save months of work by replacing bespoke data pipelines with robust pipelines that are created, orchestrated and maintained automatically. Increase your team’s efficiency by sharing features across the organization and standardize all of your machine learning data workflows in one platform. Serve features in production at extreme scale with the confidence that systems will always be up and running. Tecton meets strict security and compliance standards. Tecton is not a database or a processing engine. It plugs into and orchestrates on top of your existing storage and processing infrastructure. -
13
Hyland Document Filters
Hyland
Document Filters is an SDK that can be leveraged for various applications, such as content indexing, e-discovery, data migration, feeding data into AI/ML models and much more by extracting data from unstructured sources. It gives software developers the ability to perform deep inspection, data extraction, output manipulation and conversion for virtually any type of document and language. -
14
JetBrains Fleet
JetBrains
Built from scratch, based on 20 years of experience developing IDEs. JetBrains Fleet uses the IntelliJ code-processing engine, with a distributed IDE architecture and a reimagined UI. We built Fleet to be a fast and lightweight text editor for when you need to quickly browse and edit your code. It starts up in an instant so you can begin working immediately, and it can easily transform into an IDE, with the IntelliJ code-processing engine running separately from the editor itself. Fleet inherits the things that developers love the most from IntelliJ-based IDEs – project and context aware code completion, navigation to definitions and usages, on-the-fly code quality checks, and quick-fixes. Fleet’s architecture is designed to support a range of configurations and workflows. You can simply run Fleet just on your machine, or move some of the processes elsewhere – for example by locating the code processing in the cloud. -
15
Dasha
Dasha
Dasha is a conversational AI-as-a-service platform that lets you embed realistic voice and text conversational capabilities into your apps or products. With a single integration, create smart conversational apps for web, desktop, mobile, IoT, and call centers. DashaScript is an event-driven declarative programming language used to design complex real-world conversations that pass a limited Turing test. Automate call center conversations, recreate the Google Duplex demo in under 400 lines of code or create a no-code GUI for your users that translates into DashaScript code. If it is connected to the internet and has access to a speaker/mic, it can run a Dasha application. Your conversational voice/chat apps use your existing infrastructure, including databases, external services (Airtable, Zendesk, TalkDesk, etc.), and business logic. Run conversations through anything. Feed your custom data into Dasha and consume results where they provide the most value. -
16
JetBrains DataSpell
JetBrains
Switch between command and editor modes with a single keystroke. Navigate over cells with arrow keys. Use all of the standard Jupyter shortcuts. Enjoy fully interactive outputs – right under the cell. When editing code cells, enjoy smart code completion, on-the-fly error checking and quick-fixes, easy navigation, and much more. Work with local Jupyter notebooks or connect easily to remote Jupyter, JupyterHub, or JupyterLab servers right from the IDE. Run Python scripts or arbitrary expressions interactively in a Python Console. See the outputs and the state of variables in real-time. Split Python scripts into code cells with the #%% separator and run them individually as you would in a Jupyter notebook. Browse DataFrames and visualizations right in place via interactive controls. All popular Python scientific libraries are supported, including Plotly, Bokeh, Altair, ipywidgets, and others.Starting Price: $229 -
17
StarCoder
BigCode
StarCoder and StarCoderBase are Large Language Models for Code (Code LLMs) trained on permissively licensed data from GitHub, including from 80+ programming languages, Git commits, GitHub issues, and Jupyter notebooks. Similar to LLaMA, we trained a ~15B parameter model for 1 trillion tokens. We fine-tuned StarCoderBase model for 35B Python tokens, resulting in a new model that we call StarCoder. We found that StarCoderBase outperforms existing open Code LLMs on popular programming benchmarks and matches or surpasses closed models such as code-cushman-001 from OpenAI (the original Codex model that powered early versions of GitHub Copilot). With a context length of over 8,000 tokens, the StarCoder models can process more input than any other open LLM, enabling a wide range of interesting applications. For example, by prompting the StarCoder models with a series of dialogues, we enabled them to act as a technical assistant.Starting Price: Free -
18
PromptIDE
xAI
The xAI PromptIDE is an integrated development environment for prompt engineering and interpretability research. It accelerates prompt engineering through an SDK that allows implementing complex prompting techniques and rich analytics that visualize the network's outputs. We use it heavily in our continuous development of Grok. We developed the PromptIDE to give transparent access to Grok-1, the model that powers Grok, to engineers and researchers in the community. The IDE is designed to empower users and help them explore the capabilities of our large language models (LLMs) at pace. At the heart of the IDE is a Python code editor that - combined with a new SDK - allows implementing complex prompting techniques. While executing prompts in the IDE, users see helpful analytics such as the precise tokenization, sampling probabilities, alternative tokens, and aggregated attention masks. The IDE also offers quality of life features. It automatically saves all prompts.Starting Price: Free -
19
Pathway
Pathway
Pathway is a Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG. Pathway comes with an easy-to-use Python API, allowing you to seamlessly integrate your favorite Python ML libraries. Pathway code is versatile and robust: you can use it in both development and production environments, handling both batch and streaming data effectively. The same code can be used for local development, CI/CD tests, running batch jobs, handling stream replays, and processing data streams. Pathway is powered by a scalable Rust engine based on Differential Dataflow and performs incremental computation. Your Pathway code, despite being written in Python, is run by the Rust engine, enabling multithreading, multiprocessing, and distributed computations. All the pipeline is kept in memory and can be easily deployed with Docker and Kubernetes. -
20
Gurobi Optimizer
Gurobi Optimization
With our powerful algorithms, you can add complexity to your model to better represent the real world, and still solve your model within the available time. Integrate Gurobi into your applications easily, using the languages you know best. Our programming interfaces are designed to be lightweight, modern, and intuitive, to minimize your learning curve while maximizing your productivity. Our Python API includes higher-level modeling constructs that make it easier to build optimization models. Choose from Anaconda Python distributions with pre-built libraries to support application development, Spyder for graphical development, and Jupyter for notebook-style development. -
21
AI Crypto-Kit
Composio
AI Crypto-Kit empowers developers to build crypto agents by seamlessly integrating leading Web3 platforms like Coinbase, OpenSea, and more to automate real-world crypto/DeFi workflows. Developers can build AI-powered crypto automation in minutes, including applications such as trading agents, community reward systems, Coinbase wallet management, portfolio tracking, market analysis, and yield farming. The platform offers capabilities engineered for crypto agents, including fully managed agent authentication with support for OAuth, API keys, JWT, and automatic token refresh; optimization for LLM function calling to ensure enterprise-grade reliability; support for over 20 agentic frameworks like Pippin, LangChain, and LlamaIndex; integration with more than 30 Web3 platforms, including Binance, Aave, OpenSea, and Chainlink; and SDKs and APIs for agentic app interactions, available in Python and TypeScript. -
22
Steev
Steev
Steev is an AI training assistant that manages your training runs, eliminating the need for constant supervision and enhancing model performance. It reviews and analyzes your code before training begins, identifying potential errors, providing fixes, and suggesting better approaches to improve your workflow and outcomes. Steev takes proactive steps, adjusts training parameters, and resolves issues before they escalate, going beyond mere observation. Tracking all key variables during training, Steev sends instant notifications when your attention is needed, eliminating constant progress checks. Everything you need for smarter training is built into Steev, ready to go with zero setup required. You can try Steev for free during their beta program. -
23
GPT Pilot
Pythagora
GPT Pilot is an open-source AI tool that acts as a full AI developer, capable of generating production-ready applications with minimal human input. Unlike simple code autocompletion tools, GPT Pilot can write complete features, debug code, communicate about issues, and even request code reviews. This tool aims to push the boundaries of AI-assisted software development by handling up to 95% of coding tasks, while leaving the final 5% to developers. It’s built to integrate with platforms like VS Code, enabling developers to collaborate seamlessly with AI in real-time.Starting Price: Free -
24
smol developer
smol developer
smol-developer is an open-source library that enables developers to integrate a powerful AI-powered "junior developer" agent into their applications. This agent uses natural language processing to generate, scaffold, and assist with the development of code. Unlike conventional approaches, smol-developer allows for a more interactive development process, where the AI agent iterates and refines the code based on feedback, making it ideal for building project-specific scaffolds and automating repetitive tasks. Developers can leverage this tool to speed up the development cycle, create customized codebases, and collaborate with AI on development tasks in real-time.Starting Price: Free -
25
DeepSeek R2
DeepSeek
DeepSeek R2 is the anticipated successor to DeepSeek R1, a groundbreaking AI reasoning model launched in January 2025 by the Chinese AI startup DeepSeek. Building on R1’s success, which disrupted the AI industry with its cost-effective performance rivaling top-tier models like OpenAI’s o1, R2 promises a quantum leap in capabilities. It is expected to deliver exceptional speed and human-like reasoning, excelling in complex tasks such as advanced coding and high-level mathematical problem-solving. Leveraging DeepSeek’s innovative Mixture-of-Experts architecture and efficient training methods, R2 aims to outperform its predecessor while maintaining a low computational footprint, potentially expanding its reasoning abilities to languages beyond English.Starting Price: Free -
26
Amazon Q Business
Amazon
Amazon Q Business is a fully managed, generative AI–powered assistant designed to help employees find information, gain insights, and take action at work. It enables users to interact using natural language to request information, generate content, or create lightweight apps that automate workflows. It provides a unified search experience across systems and data, delivering quick, accurate, and relevant answers to complex questions based on documents, images, audio, and video files, and other application data, with results including citations and references for transparency. Users can interact with Amazon Q Business through its web-based conversational interface in browsers like Microsoft Edge, Google Chrome, and Mozilla Firefox, as well as in applications like Slack, Microsoft Outlook, Word for Microsoft 365, and Microsoft Teams. With Amazon Q Apps, users can automate prompting, content creation, workflows, and tasks by describing requirements in their own words.Starting Price: $20 per month -
27
AiXcoder
AiXcoder
Leave Artificial Intelligence to AIXcoder. Leave Real Intelligence to Human. The offline version is released! Your code is safe on your computer locally. AiXcoder works in smooth locally with state of art deep learning model compression techniques. The models are trained with a massive amount of open source code. And adapted to several areas. A search window is seamlessly integrated into IDE with the ability to search open-source code on GitHub. Deep learning is used to filter high-quality code as search results. Search API usage and examples. Search similar code to avoid duplicated coding. Project Level Personalized Training: Train models on personal project and computer. Enterprise Level Customized Training: Train models on code base and enterprise server. Based on standard model, personalized and customized training will learn the patterns and rules in your proprietary code. -
28
Feast
Tecton
Make your offline data available for real-time predictions without having to build custom pipelines. Ensure data consistency between offline training and online inference, eliminating train-serve skew. Standardize data engineering workflows under one consistent framework. Teams use Feast as the foundation of their internal ML platforms. Feast doesn’t require the deployment and management of dedicated infrastructure. Instead, it reuses existing infrastructure and spins up new resources when needed. You are not looking for a managed solution and are willing to manage and maintain your own implementation. You have engineers that are able to support the implementation and management of Feast. You want to run pipelines that transform raw data into features in a separate system and integrate with it. You have unique requirements and want to build on top of an open source solution. -
29
Lexalytics
Lexalytics
Integrate our text analytics APIs to add world-leading NLP into your product, platform, or application. The most feature-complete NLP feature stack on the market, 19 years in development and constantly being improved with new libraries, configurations, and models. Determine whether a piece of writing is positive, negative, or neutral. Sort and organize documents into customizable groups. Determine the expressed intent of customers and reviewers. Find people, places, dates, companies, products, jobs, titles, and more. Deploy our text analytics and NLP systems across any combination of on-premise, private cloud, hybrid cloud, and public cloud infrastructure. Our core text analytics and natural language processing software libraries are at your command. Suitable for data scientists and architects who want complete access to the underlying technology or who need on-premise deployment for security or privacy reasons. -
30
Salience
Lexalytics
Text analytics and NLP software libraries for on-premise deployment or integration. Integrate Salience into your enterprise business intelligence architecture or white label it inside your own data analytics product. Salience can process 200 tweets per second while scaling from single process cores to entire data centers with a small memory footprint. Use Java, Python, .NET/C# bindings for higher level ease or the native C/C++ interface for maximum speed. Enjoy full access to the underlying technology. Tune every text analytics function and NLP feature, from tokenization and part of speech tagging to sentiment scoring, categorization, theme analysis, and more. Built on a pipeline model of NLP rules and machine learning models. When issues arise, see exactly where they are in the pipeline. Adjust specific features without disrupting the larger system. Salience runs entirely on your servers while staying flexible enough to offload insensitive data to cloud servers.
